Nanoparticle shape effects on squeezed MHD flow of water based Cu, Al2O3 and SWCNTs over a porous sensor surface

Kandasamy, R.; Adnan, Nur Atikah bt; Mohammad, Radiah

doi:10.1016/j.aej.2017.03.011

Cited by 26 publications

(9 citation statements)

References 45 publications

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“…Study by Bahiraei et al, [5] showed that the higher thermal conductivity of nanofluids compared to ordinary liquids results in lower thermal resistance, and hence, leads to more significant heat transfer rates. Furthermore, the improvement in thermal conductivity of nanofluids can be correlated with different properties such as volume fraction, material type, size, and shape [6][7].…”

Section: Introductionmentioning

confidence: 99%

Investigation of Nanoparticles Shape Effects on Aligned MHD Casson Nanofluid Flow and Heat Transfer with Convective Boundary Condition

Bosli

Suhaimi

Ishak

et al. 2022

ARFMTS

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This study focuses on the investigation of aligned MHD natural convection flow and heat transfer of a Casson nanofluid past a vertical plate with convective boundary condition. Casson nanofluid are found in a wide range of commercial and technological applications, including dissolved polymers, biological solutions, paints, asphalts, and glues. The governing partial differential equations (PDE) is transformed to ordinary differential equations (ODE) by using similarity transformation. Keller box method is employed to numerically solve the transformed partial differential equations and then the system is solved by Fortran programming. The results for both the velocity and temperature profiles of Casson nanofluid as well as the skin friction and Nusselt number that are affected by nanoparticles shape factor considering parameters aligned angle of magnetic, interaction of magnetic field, volume fraction of nanoparticles, Local Grashof number, Casson parameter and Biot number are presented graphically and in tabulated form. It is also found that the velocity increases while the temperature decreases when the aligned angle of magnetic, interaction of magnetic field, Casson parameter and Local Grashof number increase. The skin friction and Nusselt number increases for all parameters except for Casson nanofluid parameter. For convective boundary condition, Biot number increases when both velocity and temperature profiles increase. The nanoparticles shape of laminar has the highest velocity and temperature while the spherical shape has the lowest for all parameters.

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Section: Introductionmentioning

confidence: 99%

Investigation of Nanoparticles Shape Effects on Aligned MHD Casson Nanofluid Flow and Heat Transfer with Convective Boundary Condition

Bosli

Suhaimi

Ishak

et al. 2022

ARFMTS

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“…The current analysis technique describes the flow of a water-based HBNF ( Mo S 2 + GO / water ) on a curved nonlinear stretching surface, including the characteristics of heterogeneous–homogeneous reactions and melting heat. To the best of our knowledge, 41–45 nobody has previously tried to investigate HBNF flow over a curved nonlinear stretchable surface with melting heat effects and homogeneous–heterogeneous reactions with shape factors. The associated problems have been modeled first and then analyzed using the MATLAB bvp4c solver to provide numerical results.…”

Section: Introductionmentioning

confidence: 99%

Effects of first-order chemical reaction and melting heat on hybrid nanoliquid flow over a nonlinear stretched curved surface with shape factors

Hussain

Muhammad

Anwar³

2021

Advances in Mechanical Engineering

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The aim of the current study is to disclose the results of shape factor analysis of the flow of a hybrid nanofluid over a curved sheet. The flow is caused by a stretchable curved sheet. Mathematical modeling and analyses have been performed in the presence of curvature, melting heat and heterogeneous-homogeneous reactions. Autocatalysis and the coefficients of the reactant are dealt with in a similar manner. The physical properties of the fluid, including the fluid velocity, the heat and mass transfer properties, the skin friction and the Nusselt number have been acquired and analyzed under the influences of the dimensionless curvature, melting and heterogeneous–homogeneous reaction variables. Boundary layer approximations are used in the mathematical formulation. Suitable transformations have been used to transform differential equations into nonlinear ordinary differential equations. The resulting nonlinear system of equations has been analyzed via the matlab bvp4c solver. Comparisons of nanoliquids with the hybrid nanoliquid are presented through graphs and tables. The results of this analysis show that the skin friction and the heat transfer rate in the hybrid nanofluid are seen more prominently than those of the nanofluid for larger values of the curvature parameter [Formula: see text].

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“…Venkateswarlu et al [21] discussed the impact of variable viscosity along with viscous dissipation on the flow of Cu-Al 2 O 3 /H 2 O hybrid fluid with radiative heating. Ahmed et al [22] and Kandasamy et al [23] investigated the effects of the shape factor of nanoparticles on time-dependent MHD squeezed flow between two parallel plates while considering the phenomenon of viscous dissipation. The influence of several physical parameters on the velocity and temperature field has also been analyzed numerically.…”

Section: Introductionmentioning

confidence: 99%

MHD Hybrid Nanofluid Flow Due to Rotating Disk with Heat Absorption and Thermal Slip Effects: An Application of Intelligent Computing

et al. 2021

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The objective of this study is to explore the flow features and heat transfer properties of an MHD hybrid nanofluid between two parallel plates under the effects of joule heating and heat absorption/generation (MHD-HFRHT) by utilizing the computational strength of Levenberg–Marquardt Supervised Neural Networks (LM-SNNs). Similarity equations are utilized to reduce the governing PDEs into non-linear ODEs. A reference solution in the form of data sets for MHD-HFRHT flow is obtained by creating different scenarios by varying involved governing parameters such as the Hartman number, rotation parameter, Reynolds number, velocity slip parameter, thermal slip parameter and Prandtl number. These reference data sets for all scenarios are placed for training, validation and testing through LM-SNNs and the obtained results are then compared with reference output to validate the accuracy of the proposed solution methodology. AI-based computational strength with the applicability of LM-SNNs provides an accurate and reliable source for the analysis of the presented fluid-flow system, which has been tested and incorporated for the first time. The stability, performance and convergence of the proposed solution methodology are validated through the numerical and graphical results presented, based on mean square error, error histogram, regression plots and an error-correlation measurement. MSE values of up to the accuracy level of 1 × 10−11 established the worth and reliability of the computational technique. Due to an increase in the Hartmann number, a resistance was observed, resulting in a reduction in the velocity profile. This occurs as the Hartmann number measures the relative implication of drag force that derives from magnetic induction of the velocity of the fluid flow system. However, the Reynolds number accelerates in the velocity profile due to the dominating impact of inertial force.

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Nanoparticle shape effects on squeezed MHD flow of water based Cu, Al2O3 and SWCNTs over a porous sensor surface

Cited by 26 publications

References 45 publications

Investigation of Nanoparticles Shape Effects on Aligned MHD Casson Nanofluid Flow and Heat Transfer with Convective Boundary Condition

Investigation of Nanoparticles Shape Effects on Aligned MHD Casson Nanofluid Flow and Heat Transfer with Convective Boundary Condition

Effects of first-order chemical reaction and melting heat on hybrid nanoliquid flow over a nonlinear stretched curved surface with shape factors

MHD Hybrid Nanofluid Flow Due to Rotating Disk with Heat Absorption and Thermal Slip Effects: An Application of Intelligent Computing

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